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6.
Multimodel has the potential
to support both relational and
nonrelational use cases
while reducing the number of
disparate DBMS products
in an organization.
MemSQL 6

7.
the idea of a
Hadoop distribution
will become obsolete
before it reaches
the Plateau of Productivity
MemSQL 7

8.
Penetration continues to increase and organizations
should be evaluating these resources for
— cost-efﬁciency
— infrastructure simpliﬁcation and
— new use cases, such as Hybrid Transactional/
Analytical Processing (HTAP)
MemSQL 8

15.
Real-Time Data Warehouse
This use case adds a real-time component to analytics
use cases, with the aim of reducing latency — the time
lag between when data is generated and when it can be
analyzed.
MemSQL 15

64.
Why do ML in SQL?
— Train in any number of systems
— Score in the database for applications from real-time
drilling to fraud detection to personalization
— Complete certain functions within the database to
radically simplify operational infrastructure
MemSQL 64

65.
“It is a ﬁne line between
a well executed SQL query on
live data and ML/AI”
MemSQL 65

68.
Abstract: Building a Machine Learning Recommendation Engine in SQL
Modern businesses constantly seek deeper customer relationships and more
compelling experiences.
To accomplish this, companies are looking to machine learning and artiﬁcial
intelligence solutions; however, that often involves a host of new systems and
approaches.
With a modern database architecture, it is possible to build compelling machine
learning solutions with SQL, deliver real-time engagements, and rapidly move to
operational applications.
See live, how a modern database can accomplish these feats within a single
integrated solution.
MemSQL 68